Global disparities in surgeons’ workloads, academic engagement and rest periods: the on-calL shIft fOr geNEral SurgeonS (LIONESS) study

: The workload of general surgeons is multifaceted, encompassing not only surgical procedures but also a myriad of other responsibilities. From April to May 2023, we conducted a CHERRIES-compliant internet-based survey analyzing clinical practice, academic engagement, and post-on-call rest. The questionnaire featured six sections with 35 questions. Statistical analysis used Chi-square tests, ANOVA, and logistic regression (SPSS® v. 28). The survey received a total of 1.046 responses (65.4%). Over 78.0% of responders came from Europe, 65.1% came from a general surgery unit; 92.8% of European and 87.5% of North American respondents were involved in research, compared to 71.7% in Africa. Europe led in publishing research studies (6.6 ± 8.6 yearly). Teaching involvement was high in North America (100%) and Africa (91.7%). Surgeons reported an average of 6.7 ± 4.9 on-call shifts per month, with European and North American surgeons experiencing 6.5 ± 4.9 and 7.8 ± 4.1 on-calls monthly, respectively. African surgeons had the highest on-call frequency (8.7 ± 6.1). Post-on-call, only 35.1% of respondents received a day off. Europeans were most likely (40%) to have a day off, while African surgeons were least likely (6.7%). On the adjusted multivariable analysis HDI (Human Development Index) (aOR 1.993) hospital capacity > 400 beds (aOR 2.423), working in a specialty surgery unit (aOR 2.087), and making the on-call in-house (aOR 5.446), significantly predicted the likelihood of having a day off after an on-call shift. Our study revealed critical insights into the disparities in workload, access to research, and professional opportunities for surgeons across different continents, underscored by the HDI

Structural and Immunoreactivity Properties of the SARS-CoV-2 Spike Protein upon the Development of an Inactivated Vaccine

Inactivated vaccines are promising tools for tackling the COVID-19 pandemic. We applied several protocols for SARS-CoV-2 inactivation (by β-propiolactone, formaldehyde, and UV radiation) and examined the morphology of viral spikes, protein composition of the preparations, and their immunoreactivity in ELISA using two panels of sera collected from convalescents and people vaccinated by Sputnik V. Transmission electron microscopy (TEM) allowed us to distinguish wider flail-like spikes (supposedly the S-protein’s pre-fusion conformation) from narrower needle-like ones (the post-fusion state). While the flails were present in all preparations studied, the needles were highly abundant in the β-propiolactone-inactivated samples only. Structural proteins S, N, and M of SARS-CoV-2 were detected via mass spectrometry. Formaldehyde and UV-inactivated samples demonstrated the highest affinity/immunoreactivity against the convalescent sera, while β-propiolactone (1:2000, 36 h) and UV-inactivated ones were more active against the sera of people vaccinated with Sputnik V. A higher concentration of β-propiolactone (1:1000, 2 h) led to a loss of antigenic affinity for both serum panels. Thus, although we did not analyze native SARS-CoV-2 for biosafety reasons, our comparative approach helped to exclude some destructive inactivation conditions and select suitable variants for future animal research. We believe that TEM is a valuable tool for inactivated COVID-19 vaccine quality control during the downstream manufacturing process

Structural and Immunoreactivity Properties of the SARS-CoV-2 Spike Protein upon the Development of an Inactivated Vaccine

Inactivated vaccines are promising tools for tackling the COVID-19 pandemic. We applied several protocols for SARS-CoV-2 inactivation (by β-propiolactone, formaldehyde, and UV radiation) and examined the morphology of viral spikes, protein composition of the preparations, and their immunoreactivity in ELISA using two panels of sera collected from convalescents and people vaccinated by Sputnik V. Transmission electron microscopy (TEM) allowed us to distinguish wider flail-like spikes (supposedly the S-protein’s pre-fusion conformation) from narrower needle-like ones (the post-fusion state). While the flails were present in all preparations studied, the needles were highly abundant in the β-propiolactone-inactivated samples only. Structural proteins S, N, and M of SARS-CoV-2 were detected via mass spectrometry. Formaldehyde and UV-inactivated samples demonstrated the highest affinity/immunoreactivity against the convalescent sera, while β-propiolactone (1:2000, 36 h) and UV-inactivated ones were more active against the sera of people vaccinated with Sputnik V. A higher concentration of β-propiolactone (1:1000, 2 h) led to a loss of antigenic affinity for both serum panels. Thus, although we did not analyze native SARS-CoV-2 for biosafety reasons, our comparative approach helped to exclude some destructive inactivation conditions and select suitable variants for future animal research. We believe that TEM is a valuable tool for inactivated COVID-19 vaccine quality control during the downstream manufacturing process

Genetic structure of the Balto-Slavic populations within a European context according to the three genetic systems.

<p>a) PC1vsPC3 plot based on autosomal SNPs (PC1 = 0.53; PC3 = 0.26); b) MDS based on NRY data (stress = 0.13); c) MDS based on mtDNA data (stress = 0.20). We focus on PC1<i>vs</i>PC3 because PC2 (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135820#pone.0135820.s002" target="_blank">S1 Fig</a>) whilst differentiating the Volga region populations from the rest of Europeans had a low efficiency in detecting differences among the Balto-Slavic populations–the primary focus of this work.</p

The Balto-Slavic populations analyzed in this study and the tree of Balto-Slavic languages.

<p>The map (lower panel) shows the geographical distribution of Balto-Slavic populations (colored areas) within Europe. The symbols on the map represent the geographic location of the populations genotyped. The map was created in the GeneGeo software as described previously [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135820#pone.0135820.ref068" target="_blank">68</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135820#pone.0135820.ref075" target="_blank">75</a>]. A manually constructed consensus phylogenetic tree of the Balto-Slavic languages (upper panel) is based on the StarlingNJ, NJ, BioNJ, UPGMA, Bayesian MCMC, Unweighted Maximum Parsimony methods. Ternary nodes resulting from neighboring binary nodes were joined together if the temporal distance between them was ≤ 300 years. StarlingNJ dates are proposed (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135820#pone.0135820.s008" target="_blank">S2 File</a>).</p

ADMIXTURE plot (k = 6).

<p>Ancestry proportions of 1,194 individuals as revealed by ADMIXTURE.</p

Distribution of the average number of IBD segments between groups of East-West Slavs (a), South Slavs (b), and their respective geographic neighbors.

<p>The x-axis indicates ten classes of IBD segment length (in cM); the y-axis indicates the average number of shared IBD segments per pair of individuals within each length class.</p

Correlations between matrices of genetic, geographic and linguistic distances among Balto-Slavic populations.

<p>Correlations between matrices of genetic, geographic and linguistic distances among Balto-Slavic populations.</p

Genetic Heritage of the Balto-Slavic Speaking Populations: A Synthesis of Autosomal, Mitochondrial and Y-Chromosomal Data

The Slavic branch of the Balto-Slavic sub-family of Indo-European languages underwent rapid divergence as a result of the spatial expansion of its speakers from Central-East Europe, in early medieval times. This expansion–mainly to East Europe and the northern Balkans–resulted in the incorporation of genetic components from numerous autochthonous populations into the Slavic gene pools. Here, we characterize genetic variation in all extant ethnic groups speaking Balto-Slavic languages by analyzing mitochondrial DNA (n = 6,876), Y-chromosomes (n = 6,079) and genome-wide SNP profiles (n = 296), within the context of other European populations. We also reassess the phylogeny of Slavic languages within the Balto-Slavic branch of Indo-European. We find that genetic distances among Balto-Slavic populations, based on autosomal and Y-chromosomal loci, show a high correlation (0.9) both with each other and with geography, but a slightly lower correlation (0.7) with mitochondrial DNA and linguistic affiliation. The data suggest that genetic diversity of the present-day Slavs was predominantly shaped in situ, and we detect two different substrata: ‘central-east European’ for West and East Slavs, and ‘south-east European’ for South Slavs. A pattern of distribution of segments identical by descent between groups of East-West and South Slavs suggests shared ancestry or a modest gene flow between those two groups, which might derive from the historic spread of Slavic people